Semi-supervised Facial Affective Behavior Analysis (ABAW2021 submission)

(Submission to the Affective Behavior Analysis in-the-wild (ABAW) 2021 competition)

This repository presents a multi-task mean teacher model for semi-supervised Affective Behavior Analysis to learn from missing labels and exploring the learning of multiple correlated task simultaneously.

For more detail, please check our paper: Arxiv.

Required packages

torch 1.6.0, torchaudio 0.6, tqdm, Numpy, OpenCV 4.2.0, lmdb

Testing

To predict on competition test set, download our model and alignment files:

Alignment_face,Model Weight,Alignment data can be download here with extract code: wk36

Clone the repository,then download above data and config their path in opts.py before running

python test_val_aff2.py

Citation

Our paper have been submitted to Arxiv.

This repository is based on TSAV, thanks to their excellent work. Please cite their paper of TSAV if this respority helps you.